The current state of the art in mixing of biogas digesters is described and the areas where future research needs to be concentrated are outlined. Since mixing is the biggest contributor to energy consumption in digesters, it is important to optimize it in order to improve the overall cost-effectiveness of biodigestion. This optimization problem is a large-scale nonlinear mixed-integer problem with many decision variables. Also, an artificial substrate for lab-scale experimental studies on digester mixing is introduced. This artificial substrate has several properties crucial for the task like rheological behavior which allows for transferring the results of the labscale experiments to full scale, transparency to observe flow patterns, and thus, quantify the degree of mixing, stability preventing the substrate to change its rheological properties over time, and lack of any health hazards.
Mixing in Biogas Digesters and Development of an Artificial Substrate for Laboratory-Scale Mixing Optimization
CONTI, FOSCA;
2017
Abstract
The current state of the art in mixing of biogas digesters is described and the areas where future research needs to be concentrated are outlined. Since mixing is the biggest contributor to energy consumption in digesters, it is important to optimize it in order to improve the overall cost-effectiveness of biodigestion. This optimization problem is a large-scale nonlinear mixed-integer problem with many decision variables. Also, an artificial substrate for lab-scale experimental studies on digester mixing is introduced. This artificial substrate has several properties crucial for the task like rheological behavior which allows for transferring the results of the labscale experiments to full scale, transparency to observe flow patterns, and thus, quantify the degree of mixing, stability preventing the substrate to change its rheological properties over time, and lack of any health hazards.| File | Dimensione | Formato | |
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Mixing in Biogas Digesters and development of an artificial substrate for laboratory-scale mixing optimization_CET2017.pdf
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